1. Field of Invention
The present invention pertains to the field of device testing. More particularly, this invention relates to a model-based diagnostic system that provides automated tools for selection of one or more next tests to apply to a device under test.
2. Art Background
A wide variety of systems including mechanical, electrical and chemical systems as well a combinations thereof are commonly tested under a variety of environments including manufacturing test environments and field support environments. These systems include electronic systems such as circuit boards and full systems having a variety of circuit boards. These systems also include automobiles, satellite systems, and test equipment. Such a system while undergoing a test cycle may be referred to as a device under test (DUT).
Such a DUT typically includes a variety of components. Such components include, for example, integrated circuit devices, electrical components, battery systems, mechanical components, electrical buses, wiring components, and wiring harness and backplane components. Any one or more of such components may fail and cause a failure of the DUT.
Prior diagnostic systems for determining likely failed components in a DUT include model-based diagnostic systems. A model-based diagnostic system may be defined as a diagnostic system that renders conclusions about the state of the DUT using actual DUT responses from applied tests as an input to the diagnostic system. Such a diagnostic system is usually based upon computer generated models of the DUT and its components and the diagnostic process.
It is usually desirable to employ a model-based diagnostic system that is based upon a more manageable model of DUT characteristics. Such a model-based diagnostic system usually minimizes the amount of modeling information for a DUT that must be generated by a user before the system can be applied to the DUT. Such modeling usually speeds the process of adapting the diagnostic system to differing DUTs and increases confidence in the determinations rendered by the diagnostic system.
U.S. patent application Ser. No. 08/551,054 of Preist et. al. discloses a model-based diagnostic system, based on functional tests, in which the modeling burden is greatly reduced. The model disclosed in Preist et. al. employs a list of functional tests, a list of components exercised by each functional test along with the degree to which each component is exercised by each functional test, and (if available) the historical or a priori failure rate for individual components. Such model data may be rapidly and easily determined or estimated by test engineers, test programmers or others familiar with, but not necessarily expert on, the device under test. Typically, the models may be developed by test engineers in a few days to a few weeks depending on the complexity of the device under test.
The model-based diagnostic system of Preist et. al. is well-suited for a test environment that allows the automatic application of a sequence of tests to a device under test. Such a diagnostic system is particularly applicable when all available tests can be applied without a significant increase in time and cost. This situation is common in electronics manufacturing. For example, a printed circuit board can be attached to a fixture and a large number of tests can be applied before the device is removed from the fixture.
Other test environments, however, may be subject to time and/or cost constraints. For example, the application of diagnostic tests to an automobile or electronic device after sale is typically subject to time and cost constraints. Typically, only a few of the available tests can be performed economically in such a post-sale test environment. In such test environments, it is highly desirable to minimize the time required to diagnose a failure and to replace failed components. Therefore, it is highly desirable to be able to determine a next test to apply to a DUT based upon the results of earlier tests. The next test should be the best test from the point of view of eventually acheiving a correct diagnosis.
Prior model-based diagnostic systems which employ more manageable models usually do not provide automated tools for selecting a best next test. As a consequence, prior model-based diagnostic systems may impose excessive and expensive down time of the DUT during application of tests that are not necessarily the best next test to apply. Moreover, such prior systems usually do not provide tools for taking into account the economic costs associated with performing particular tests or replacing particular components of the device under test.